Titlebook: Risk and Capital; Proceedings of the 2 Günter Bamberg,Klaus Spremann Conference proceedings 1984 Springer-Verlag Berlin Heidelberg 1984 Kap

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Mis-Specifications in Portfolio Selection Problemsblems. These mis-specifications can occur in three areas: the investor’s utility function, and the mean vector and covariance matrix of the return distribution. Our results suggest that only the second type of error will create significant problems in applications.

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Increasing Multivariate Risk: Some Definitionsly distributed multivariate prospects with equal as well as unequal mean vectors. In addition, two multivariate versions of increasing variance are considered. The relations between the multivariate notions correspond very closely to known relations between the univariate ones. For multinormal prosp

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A Firm in Statu Nascendi — Initial and Final Shareholdersith two problems: Firstly, an investment decision must determine the size in which the object of investment should be realized. This is the question of the production plan. Secondly, the corresponding amount of capital must be taken up through the issue of new shares.

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Reserve Levels and Reserve Requirements for Profit-Maximizing Insurance Firmsion for such reserve requirements is usually based on consumer ignorance; it is alleged to be costly if not impossible for a typical consumer of insurance to determine the level of reserves held by insurance firms from which he buys; consequently, consumers would often be unprepared for insurer defa

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Financial Planning Via Stochastic Programming: A Stochastic Flows-With-Gains Approachof network flow formulations will increase the readiness of adoption of mathematical programming procedures in this area..The possibility of using flows-with-gains for the formulation of financial decisions is known but its combination with stochastic programming, which allows a more realistic descr

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Optimization Models for Distribution Planningnistic demand, several applications are described which illustrate the cost savings that can be attained with such models. Extensions to the case of stochastic demand are then given. Alternative models for distribution problems with stochastic demand are described, and the implications on computatio

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